Climate Spaces and Cliffs: A Novel Bovine Thermodynamic and Mass Balances Model.

The effects of climate change on animals are typically viewed in terms of survivability and wellbeing. In this study, we broaden that purview to include climate impacts on reproductive capability. There are not only climate spaces for daily function, but climate cliffs that represent reproductive failures in the face of climate warming. This alternative focus suggests that climate warming challenges may be more immediate and profound than initially imagined. This research describes a state-of-the-art mechanistic model, Dairy Niche Mapper (DNM), and independent validation tests. Where test data are absent, the calculated results are consistent with expected responses. Simulations of metabolic chamber conditions reveal the local steady-state impacts of climate and animal variables on milk production capacity, metabolic rate, food consumption and water needs. Simulations of a temperature humidity index (THI) show strengths and limitations of that approach. Broader time- and spatial-scale calculations applied in the western and eastern halves of the northern hemisphere identify current and future monthly latitudinal climate change impacts on milk production potential, feed and water needs in dairy cows of different sizes. Dairy Niche Mapper (DNM) was developed from a broadly tested mechanistic microclimate-animal model, Niche Mapper (NM). DNM provides an improved quantitative understanding of the complex nonlinear interactions of climate variation and dairy bovine properties' effects on current and future milk production, feed and water needs for grazing and confinement dairy operations. DNM outputs include feasible activity times, milk production and water and feed needs of different-sized Holstein cows on high-grain (confinement feeding) versus high-forage (grazing feeding) diets at three arbitrary north latitudes, 12°, 30° and 60°, for North and Central America and for Asia. These three latitudes encompass current northern hemisphere bovine production environments and possible future production locations. The greatest impacts of climate change will be in the low elevations in tropical and subtropical regions. Global regions above 30° and below 60° latitude with reliable rainfall will be least affected by current projected levels of climate change. This work provides the basis for computational animal design for guiding agricultural development via breeding programs, genetic engineering, management options including siting or the manipulation of other relevant environmental and animal variables.

Incorporating species-specific morphology improves model predictions of thermal and hydric stress in the sand fiddler crab, Leptuca pugilator.

Understanding where and why organisms are experiencing thermal and hydric stress is critical for predicting species' responses to climate change. Biophysical models that explicitly link organismal functional traits like morphology, physiology, and behavior to environmental conditions can provide valuable insight into determinants of thermal and hydric stress. Here we use a combination of direct measurements, 3D modeling, and computational fluid dynamics to develop a detailed biophysical model of the sand fiddler crab, Leptuca pugilator. We compare the detailed model's performance to a model using a simpler ellipsoidal approximation of a crab. The detailed model predicted crab body temperatures within 1 °C of observed in both laboratory and field settings; the ellipsoidal approximation model predicted body temperatures within 2 °C of observed body temperatures. Model predictions are meaningfully improved through efforts to incorporate species-specific morphological properties rather than relying on simple geometric approximations. Experimental evaporative water loss (EWL) measurements indicate that L. pugilator can modify its permeability to EWL as a function of vapor density gradients, providing novel insight into physiological thermoregulation in the species. Body temperature and EWL predictions made over the course of a year at a single site demonstrate how such biophysical models can be used to explore mechanistic drivers and spatiotemporal patterns of thermal and hydric stress, providing insight into current and future distributions in the face of climate change.

Mechanistic forecasts of species responses to climate change: The promise of biophysical ecology.

A core challenge in global change biology is to predict how species will respond to future environmental change and to manage these responses. To make such predictions and management actions robust to novel futures, we need to accurately characterize how organisms experience their environments and the biological mechanisms by which they respond. All organisms are thermodynamically connected to their environments through the exchange of heat and water at fine spatial and temporal scales and this exchange can be captured with biophysical models. Although mechanistic models based on biophysical ecology have a long history of development and application, their use in global change biology remains limited despite their enormous promise and increasingly accessible software. We contend that greater understanding and training in the theory and methods of biophysical ecology is vital to expand their application. Our review shows how biophysical models can be implemented to understand and predict climate change impacts on species' behavior, phenology, survival, distribution, and abundance. It also illustrates the types of outputs that can be generated, and the data inputs required for different implementations. Examples range from simple calculations of body temperature at a particular site and time, to more complex analyses of species' distribution limits based on projected energy and water balances, accounting for behavior and phenology. We outline challenges that currently limit the widespread application of biophysical models relating to data availability, training, and the lack of common software ecosystems. We also discuss progress and future developments that could allow these models to be applied to many species across large spatial extents and timeframes. Finally, we highlight how biophysical models are uniquely suited to solve global change biology problems that involve predicting and interpreting responses to environmental variability and extremes, multiple or shifting constraints, and novel abiotic or biotic environments.

Behavioural responses of a large, heat-sensitive mammal to climatic variation at multiple spatial scales.

Climate warming creates energetic challenges for endothermic species by increasing metabolic and hydric costs of thermoregulation. Although endotherms can invoke an array of behavioural and physiological strategies for maintaining homeostasis, the relative effectiveness of those strategies in a climate that is becoming both warmer and drier is not well understood. In accordance with the heat dissipation limit theory which suggests that allocation of energy to growth and reproduction by endotherms is constrained by the ability to dissipate heat, we expected that patterns of habitat use by large, heat-sensitive mammals across multiple scales are critical for behavioural thermoregulation during periods of potential heat stress and that they must invest a large portion of time to maintain heat balance. To test our predictions, we evaluated mechanisms underpinning the effectiveness of bed sites for ameliorating daytime heat loads and potential heat stress across the landscape while accounting for other factors known to affect behaviour. We integrated detailed data on microclimate and animal attributes of moose Alces alces, into a biophysical model to quantify costs of thermoregulation at fine and coarse spatial scales. During summer, moose spent an average of 67.8% of daylight hours bedded, and selected bed sites and home ranges that reduced risk of experiencing heat stress. For most of the day, shade could effectively mitigate the risk of experiencing heat stress up to 10°C, but at warmer temperatures (up to 20°C) wet soil was necessary to maintain homeostasis via conductive heat loss. Consistent selection across spatial scales for locations that reduced heat load underscores the importance of the thermal environment as a driver of behaviour in this heat-sensitive mammal. Moose in North America have long been characterized as riparian-obligate species because of their dependence on woody plant species for food. Nevertheless, the importance of dissipating endogenous heat loads conductively through wet soil suggests riparian habitats also are critical thermal refuges for moose. Such refuges may be especially important in the face of a warming climate in which both high environmental temperatures and drier conditions will likely exacerbate limits to heat dissipation, especially for large, heat-sensitive animals.

Physiological costs of undocumented human migration across the southern United States border.

Political, economic, and climatic upheaval can result in mass human migration across extreme terrain in search of more humane living conditions, exposing migrants to environments that challenge human tolerance. An empirical understanding of the biological stresses associated with these migrations will play a key role in the development of social, political, and medical strategies for alleviating adverse effects and risk of death. We model physiological stress associated with undocumented migration across a commonly traversed section of the southern border of the United States and find that locations of migrant death are disproportionately clustered within regions of greatest predicted physiological stress (evaporative water loss). Minimum values of estimated evaporative water loss were sufficient to cause severe dehydration and associated proximate causes of mortality. Integration of future climate predictions into models increased predicted physiological costs of migration by up to 34.1% over the next 30 years.

North Atlantic winter cyclones starve seabirds.

Each winter, the North Atlantic Ocean is the stage for numerous cyclones, the most severe ones leading to seabird mass-mortality events called "winter wrecks."1-3 During these, thousands of emaciated seabird carcasses are washed ashore along European and North American coasts. Winter cyclones can therefore shape seabird population dynamics4,5 by affecting survival rates as well as the body condition of surviving individuals and thus their future reproduction. However, most often the geographic origins of impacted seabirds and the causes of their deaths remain unclear.6 We performed the first ocean-basin scale assessment of cyclone exposure in a seabird community by coupling winter tracking data for ∼1,500 individuals of five key North Atlantic seabird species (Alle alle, Fratercula arctica, Uria aalge, Uria lomvia, and Rissa tridactyla) and cyclone locations. We then explored the energetic consequences of different cyclonic conditions using a mechanistic bioenergetics model7 and tested the hypothesis that cyclones dramatically increase seabird energy requirements. We demonstrated that cyclones of high intensity impacted birds from all studied species and breeding colonies during winter but especially those aggregating in the Labrador Sea, the Davis Strait, the surroundings of Iceland, and the Barents Sea. Our broad-scale analyses suggested that cyclonic conditions do not increase seabird energy requirements, implying that they die because of the unavailability of their prey and/or their inability to feed during cyclones. Our study provides essential information on seabird cyclone exposure in a context of marked cyclone regime changes due to global warming.8.

Meeting Paris agreement objectives will temper seabird winter distribution shifts in the North Atlantic Ocean.

We explored the implications of reaching the Paris Agreement Objective of limiting global warming to <2°C for the future winter distribution of the North Atlantic seabird community. We predicted and quantified current and future winter habitats of five North Atlantic Ocean seabird species (Alle alle, Fratercula arctica, Uria aalge, Uria lomvia and Rissa tridactyla) using tracking data for ~1500 individuals through resource selection functions based on mechanistic modeling of seabird energy requirements, and a dynamic bioclimate envelope model of seabird prey. Future winter distributions were predicted to shift with climate change, especially when global warming exceed 2°C under a "no mitigation" scenario, modifying seabird wintering hotspots in the North Atlantic Ocean. Our findings suggest that meeting Paris agreement objectives will limit changes in seabird selected habitat location and size in the North Atlantic Ocean during the 21st century. We thereby provide key information for the design of adaptive marine-protected areas in a changing ocean.

Field data confirm the ability of a biophysical model to predict wild primate body temperature.

In the face of climate change there is an urgent need to understand how animal performance is affected by environmental conditions. Biophysical models that use principles of heat and mass transfer can be used to explore how an animal's morphology, physiology, and behavior interact with its environment in terms of energy, mass and water balances to affect fitness and performance. We used Niche Mapper™ (NM) to build a vervet monkey (Chlorocebus pygerythrus) biophysical model and tested the model's ability to predict core body temperature (Tb) variation and thermal stress against Tb and behavioral data collected from wild vervets in South Africa. The mean observed Tb in both males and females was within 0.5 °C of NM's predicted Tbs for 91% of hours over the five-year study period. This is the first time that NM's Tb predictions have been validated against field data from a wild endotherm. Overall, these results provide confidence that NM can accurately predict thermal stress and can be used to provide insight into the thermoregulatory consequences of morphological (e.g., body size, shape, fur depth), physiological (e.g. Tb plasticity) and behavioral (e.g., huddling, resting, shade seeking) adaptations. Such an approach allows users to test hypotheses about how animals adapt to thermoregulatory challenges and make informed predictions about potential responses to environmental change such as climate change or habitat conversion. Importantly, NM's animal submodel is a general model that can be adapted to other species, requiring only basic information on an animal's morphology, physiology and behavior.

Health and economic impact of nitrate pollution in drinking water: a Wisconsin case study.

Nitrate contamination of drinking water, common in agricultural areas, increases the risk of certain cancers and impacts fetal development during pregnancy. Building on previously published methodology, this study evaluates nitrate-attributable disease cases and adverse birth outcomes as well as their economic costs for Wisconsin, USA. Nitrate is the most common contaminant in groundwater in Wisconsin. Two-thirds of the state's residents use groundwater as the primary source of drinking water. Here, we analyze nitrate exposure from drinking water in Wisconsin based on nitrate test results for community water systems for the period of 2010-2017 and a novel methodology for estimating nitrate exposure for the 28% of state's residents who use private wells. We estimate that annually, 111-298 combined cases of colorectal, ovarian, thyroid, bladder, and kidney cancer in Wisconsin may be due to nitrate contamination of drinking water. Each year, up to 137-149 cases of very low birth weight, 72-79 cases of very preterm birth, and two cases of neural tube defects could be due to nitrate exposure from drinking water. The direct medical cost estimates for all nitrate-attributable adverse health outcomes range between $23 and $80 million annually. Simulating targeted reductions in the counties with the highest current drinking water nitrate concentrations resulted in similar reductions in adverse health outcomes as statewide reduction efforts, up to nitrate reductions of 20%. Time trend analysis suggests that groundwater nitrate concentrations are overall increasing. Thus, nitrate contamination of water supplies in Wisconsin is a public health problem that needs to be addressed.

Landscape scale thermoregulatory costs from sublethal exposure to Deep Water Horizon oil in the double-crested cormorant.

Toxic effects of heavy oiling to wildlife are well known from oil spills, although sublethal oil exposure effects are poorly understood. We used Niche Mapper™, to compute spatially and temporally specific energetic and behavioral impacts of repeated sublethal oil exposure to double-crested cormorants (Phalacrocorax auritus). During winter (October-March) cormorants exposed to 13 g, 39 g, and 65-78 g of oil, had on average a 31%, 59%, and 76% predicted increase in total resting energetic requirements (RMR) compared to unoiled birds, respectively. Increased RMR resulted in a mean (±SD) predicted increase in time spent foraging of 36 (±13) min·d-1. During the breeding season (April-September), cormorants had on average a 29%, 57% and 73% increase in total RMR and the mean predicted increase in time spent foraging was 131 (±49) min·d-1. Thermoregulatory effects of sublethal oil exposure may cause greater impacts to bird populations than is currently understood.

Modeling Dragons: Using linked mechanistic physiological and microclimate models to explore environmental, physiological, and morphological constraints on the early evolution of dinosaurs.

We employed the widely-tested biophysiological modeling software, Niche Mapper™ to investigate the metabolic function of the Late Triassic dinosaurs Plateosaurus and Coelophysis during global greenhouse conditions. We tested a variety of assumptions about resting metabolic rate, each evaluated within six microclimate models that bound paleoenvironmental conditions at 12° N paleolatitude, as determined by sedimentological and isotopic proxies for climate within the Chinle Formation of the southwestern United States. Sensitivity testing of metabolic variables and simulated "metabolic chamber" analyses support elevated "ratite-like" metabolic rates and intermediate "monotreme-like" core temperature ranges in these species of early saurischian dinosaur. Our results suggest small theropods may have needed partial to full epidermal insulation in temperate environments, while fully grown prosauropods would have likely been heat stressed in open, hot environments and should have been restricted to cooler microclimates such as dense forests or higher latitudes and elevations. This is in agreement with the Late Triassic fossil record and may have contributed to the latitudinal gap in the Triassic prosauropod record.

Climate change could overturn bird migration: Transarctic flights and high-latitude residency in a sea ice free Arctic.

Climate models predict that by 2050 the Arctic Ocean will be sea ice free each summer. Removing this barrier between the Atlantic and the Pacific will modify a wide range of ecological processes, including bird migration. Using published information, we identified 29 arctic-breeding seabird species, which currently migrate in the North Atlantic and could shift to a transarctic migration towards the North Pacific. We also identified 24 arctic-breeding seabird species which may shift from a migratory strategy to high-arctic year-round residency. To illustrate the biogeographical consequences of such drastic migratory shifts, we performed an in-depth study of little auks (Alle alle), the most numerous artic seabird. Coupling species distribution models and climatic models, we assessed the adequacy of future wintering and breeding areas for transarctic migrants and high-arctic year-round residents. Further, we used a mechanistic bioenergetics model (Niche Mapper), to compare the energetic costs of current little auk migration in the North Atlantic with potential transarctic and high-arctic residency strategies. Surprisingly, our results indicate that transarctic little auk migration, from the North Atlantic towards the North Pacific, may only be half as costly, energetically, than high-arctic residency or migration to the North Atlantic. Our study illustrates how global warming may radically modify the biogeography of migratory species, and provides a general methodological framework linking migratory energetics and spatial ecology.

Mechanistic modeling of environmental drivers of woolly mammoth carrying capacity declines on St. Paul Island.

On St. Paul Island, a remnant of the Bering Land Bridge, woolly mammoths persisted until 5,600 yr BP with no known predators or competitors, providing a natural system for studying hypothesized environmental drivers of extinction. These include overheating due to rising temperatures, starvation, and drought. Here, we test these hypotheses using Niche Mapper and LPJ-GUESS to mechanistically estimate mammoth metabolic rates and dietary and freshwater requirements and, from these, estimate variations in island carrying capacity on St. Paul for the last 17,000 yr. Population carrying capacity may have been several hundred individuals at the time of initial isolation from the mainland. Adult mammoths could have fasted for two to three months, indicating a necessary ability to access snow-buried forage. During the Holocene, vegetation net primary productivity increased, but shrinking island area overrode increased net primary productivity (NPP), lowering carrying capacity to ~100 individuals. NPP and freshwater availability alternated as critical limiting factors for this island population during the environmental changes of the late Pleistocene and Holocene. Only two or three individuals could have been sustained by the freshwater surplus in crater lakes (up to 18 individuals under the most optimistic parameter sensitivity experiments), suggesting that the St. Paul mammoth population was highly dependent on coastal freshwater sources. The simulations are consistent with the available proxy data, while highlighting the need to retrieve new paleohydrological proxy records from the coastal lagoons to test model predictions. More broadly, these findings reinforce the vulnerability of island megaherbivore populations to resource limitation and extinction.

Experimental and modeled thermoregulatory costs of repeated sublethal oil exposure in the Double-crested Cormorant, Phalacrocorax auritus.

To fully understand the impact of oil exposure, it is important to understand sublethal effects like how increased thermoregulatory costs may affect survival and reproduction. However, it is difficult and time-consuming to measure these effects in wild animals. We present a novel use of a bioenergetics model, Niche Mapper™, to estimate thermoregulatory impacts of oiling, using data from captive Double-crested Cormorants (Phalacrocorax auritus) experimentally exposed to oil. Oiled cormorants had significant increases in surface body temperatures following exposure. Niche Mapper accurately predicted surface temperatures and metabolic rates for unoiled and oiled cormorants and predicted 13-18% increased daily energetic demands due to increased thermoregulatory costs of oiling, consistent with increased food consumption observed in experimentally oiled cormorants. We show that Niche Mapper can provide valuable insight into sublethal oiling effects by quantifying the extent to which thermoregulatory costs divert energy resources away from important life processes like maintenance, reproduction and migration.

Polycyclic aromatic hydrocarbon contamination and source profiling in watersheds serving three small Wisconsin, USA cities.

Polycyclic aromatic hydrocarbons (PAHs) continue to be common environmental contaminants. The anthropogenic sources of these compounds are broadly classed as petrogenic and pyrogenic, but more importantly specific sources including activities such as coal burning, oil spills, and application of coal tar sealants can be identified based on several types of data analysis. Several studies have focused on PAHs in sediments of lakes, streams, and stormwater ponds in larger urban areas, finding contamination arising from a number of different sources and correlating well to land use in the nearby watershed. We report here a study of PAH concentrations and source identification for river and lakebed sediments in and upstream of three smaller Wisconsin municipalities: Eau Claire (Eau Claire River), Stevens Point (Plover River), and Racine (Root River). PAH concentrations increased with increasing developed land cover and impervious surface. Concentrations within the cities and upstream agricultural or residential areas do not rise to the level found in larger urban areas or stormwater ponds servicing industrial or commercial land use, but can rise to a level that exceeds the Threshold Effects Concentration (TEC). Concentrations in areas with natural landcovers were very low, with the exception of one sample in a wetland with unusually high organic content. Multiple lines of evidence indicate that coal tar-based pavement sealants are a primary source of the contamination in all three cities. PAH concentrations reported here are likely conservative, and these results indicate that even smaller cities using detention ponds as a stormwater management practice should be prepared for costs of contaminated sediment disposal.

An ecophysiological perspective on likely giant panda habitat responses to climate change.

Threatened and endangered species are more vulnerable to climate change due to small population and specific geographical distribution. Therefore, identifying and incorporating the biological processes underlying a species' adaptation to its environment are important for determining whether they can persist in situ. Correlative models are widely used to predict species' distribution changes, but generally fail to capture the buffering capacity of organisms. Giant pandas (Ailuropoda melanoleuca) live in topographically complex mountains and are known to avoid heat stress. Although many studies have found that climate change will lead to severe habitat loss and threaten previous conservation efforts, the mechanisms underlying panda's responses to climate change have not been explored. Here, we present a case study in Daxiangling Mountains, one of the six Mountain Systems that giant panda distributes. We used a mechanistic model, Niche Mapper, to explore what are likely panda habitat response to climate change taking physiological, behavioral and ecological responses into account, through which we map panda's climatic suitable activity area (SAA) for the first time. We combined SAA with bamboo forest distribution to yield highly suitable habitat (HSH) and seasonal suitable habitat (SSH), and their temporal dynamics under climate change were predicted. In general, SAA in the hottest month (July) would reduce 11.7%-52.2% by 2070, which is more moderate than predicted bamboo habitat loss (45.6%-86.9%). Limited by the availability of bamboo and forest, panda's suitable habitat loss increases, and only 15.5%-68.8% of current HSH would remain in 2070. Our method of mechanistic modeling can help to distinguish whether habitat loss is caused by thermal environmental deterioration or food loss under climate change. Furthermore, mechanistic models can produce robust predictions by incorporating ecophysiological feedbacks and minimizing extrapolation into novel environments. We suggest that a mechanistic approach should be incorporated into distribution predictions and conservation planning.

Naturally Occurring versus Anthropogenic Sources of Elevated Molybdenum in Groundwater: Evidence for Geogenic Contamination from Southeast Wisconsin, United States.

Molybdenum (Mo) is an essential trace nutrient but has negative health effects at high concentrations. Groundwater typically has low Mo (<2 µg/L), and elevated levels are associated with anthropogenic contamination, although geogenic sources have also been reported. Coal combustion residues (CCRs) are enriched in Mo, and thus present a potential anthropogenic contamination source. Here, we use diagnostic geochemical tracers combined with groundwater residence time indicators to investigate the sources of Mo in drinking-water wells from shallow aquifers in a region of widespread CCR disposal in southeastern Wisconsin. Samples from drinking-water wells were collected in areas near and away from known CCR disposal sites, and analyzed for Mo and inorganic geochemistry indicators, including boron and strontium isotope ratios, along with groundwater tritium-helium and radiogenic 4He in-growth age-dating techniques. Mo concentrations ranged from <1 to 149 µg/L. Concentrations exceeding the U.S. Environmental Protection Agency health advisory of 40 µg/L were found in deeper, older groundwater (mean residence time >300 y). The B (δ11B = 22.9 ± 3.5‰) and Sr (87Sr/86Sr = 0.70923 ± 0.00024) isotope ratios were not consistent with the expected isotope fingerprints of CCRs, but rather mimic the compositions of local lithologies. The isotope signatures combined with mean groundwater residence times of more than 300 years for groundwater with high Mo concentrations support a geogenic source of Mo to the groundwater, rather than CCR-induced contamination. This study demonstrates the utility of a multi-isotope approach to distinguish between fossil fuel-related and natural sources of groundwater contamination.

Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates.

How climate constrains species' distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8-19% less habitat loss in response to annual temperature increases of ~3-5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate-imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans.

Linking habitat selection to fitness-related traits in herbivores: the role of the energy landscape.

Animals may partially overcome environmental constraints on fitness by behaviorally adjusting their exposure to costs and supplies of energy. Few studies, however, have linked spatiotemporal variation in the energy landscape to behaviorally mediated measures of performance that ostensibly influence individual fitness. We hypothesized that strength of selection by North American elk (Cervus elaphus) for areas that reduced costs of thermoregulation and activity, and increased access to high-quality forage, would influence four energetically mediated traits related to fitness: birth mass of young, nutritional condition of adult females at the onset of winter, change in nutritional condition of females between spring and winter, and neonatal survival. We used a biophysical model to map spatiotemporally explicit costs of thermoregulation and activity experienced by elk in a heterogeneous landscape. We then combined model predictions with data on forage characteristics, animal locations, nutritional condition, and mass and survival of young to evaluate behaviorally mediated effects of the energy landscape on fitness-related traits. During spring, when high-quality forage was abundant, female elk that consistently selected low-cost areas before parturition gave birth to larger young than less-selective individuals, and birth mass had a strong, positive influence on probability of survival. As forage quality declined during autumn, however, lactating females that consistently selected the highest quality forage available accrued more fat and entered winter in better condition than less-selective individuals. Results of our study highlight the importance of understanding the dynamic nature of energy landscapes experienced by free-ranging animals.

Validation of a Mechanistic Model for Non-Invasive Study of Ecological Energetics in an Endangered Wading Bird with Counter-Current Heat Exchange in its Legs.

Mechanistic models provide a powerful, minimally invasive tool for gaining a deeper understanding of the ecology of animals across geographic space and time. In this paper, we modified and validated the accuracy of the mechanistic model Niche Mapper for simulating heat exchanges of animals with counter-current heat exchange mechanisms in their legs and animals that wade in water. We then used Niche Mapper to explore the effects of wading and counter-current heat exchange on the energy expenditures of Whooping Cranes, a long-legged wading bird. We validated model accuracy against the energy expenditure of two captive Whooping Cranes measured using the doubly-labeled water method and time energy budgets. Energy expenditure values modeled by Niche Mapper were similar to values measured by the doubly-labeled water method and values estimated from time-energy budgets. Future studies will be able to use Niche Mapper as a non-invasive tool to explore energy-based limits to the fundamental niche of Whooping Cranes and apply this knowledge to management decisions. Basic questions about the importance of counter-current exchange and wading to animal physiological tolerances can also now be explored with the model.